This article examines the theoretical and methodological foundations of applying the fuzzy regression model in assessing production efficiency in agricultural sectors. The advantages of the fuzzy approach in optimizing the utilization of available resources in the agricultural sector are analyzed. Furthermore, the scientific significance of identifying the relationships between factors affecting efficiency under conditions of uncertainty using the fuzzy regression model is theoretically substantiated.

This study is devoted to analyzing the role and importance of the innovation project management system in improving the efficiency of industrial enterprises. The essence of the innovation project management system is revealed through the features of functioning under uncertainty and creative environments in modern industry. A comparative analysis of the duration, risk level, and expected outcomes of each type of innovation is presented. The research results prove the strategic role of the innovation project management system in ensuring long-term economic growth by increasing the competitiveness of industrial enterprises, entering new markets, improving productivity, and reducing costs. The study concludes that, under modern globalization, the ability to professionally manage innovation projects is a vital necessity for industrial enterprises.